What am I missing about the example below?
Field A - Average Rating 1000 average score = 50
Field B - Average rating 950 average score = 52

Field A score 50 = 1000 rated
Field B score 52 = 950 rated the 50 would only be like 980 rated.

Hi 1978,

The missing component there is the relationship between player (initial) rating and rating-points-per-throw. The PDGA uses two linear equations to match SSA up with an (arbitrary) associated rating-points-per-throw. In order for the difference between a 950 rated player shooting an 'average' 52 and a 1000 rated player shooting an 'average' 50 means a rating-points-per-throw of 25.. much higher than either the PDGA linear compression formula or the observed slope of initial rating vs. scoring spread. Realistically, the value is typically in the 5-15 points-per-throw range, both using the PDGA compression formulas or the slope of initial rating vs. scoring spread. Does that help at all?

So, if the SSA after field A plays is determined to be 50, the rating_points_per_throw increment would be 10.21865. So a 52 would be rated at 979.5627 (rounded to 980). So your field B would be vastly more likely to average ~55 than 52. (actually 54.89301424356).

So, if the SSA after field A plays is determined to be 50, the rating_points_per_throw increment would be 10.21865. So a 52 would be rated at 979.5627 (rounded to 980). So your field B would be vastly more likely to average ~55 than 52. (actually 54.89301424356).

Can you explain the 2 tournaments played 2 weeks apart, same exact layout and conditions, basically. Am vs pro

Round 3: Pro and Adv played with extremely tight OBs and 5 longer tees, INT and lower played on the same course at the exact same time without the OBs and from the regular tees. An INTs 72 was rated higher from the easier layout than the 72s from the tougher layout.

I wish I could find the response when I asked CK about it. It was actually pretty comical, something about having to be more focused to get 2s with the added OB, thus making it easier

How is this not mostly because of the higher rated players in the open tournament padding the ratings of the rounds.

Hi 1978,

Hmm.. do you happen to have the initial ratings of all propagators/players as well as their scores for each round? Without actually graphing it all, it's tough to really see what was happening with ratings/round scores. I watched footage of that event, and the course looked like it had a fair number of really short but really technical holes, and then some longer (but still really technical) holes too. Given the better angular accuracy of gold-level players, I admit that particular 13-point gap looks odd. If anything, I'd expect it to be in the other direction (the Open field 60 would rate lower). How many players were in each event, by the way? If you can get me initial ratings and round scores, I'd be happy to make some charts and run the regression.. it may help explain it.

Edit: running a Pearson Correlation Coefficient for the rounds may prove interesting, too. Heavily wooded courses tend to have low(er) correlation coefficients (the predictive value of initial player rating vs event score).. i.e. they tend to induce a lot more randomness into round scores than less wooded courses).

How is this not mostly because of the higher rated players in the open tournament padding the ratings of the rounds.

I think I can explain this very easy - without using fancy charts, regression, or even a Pearson Correlation Coefficient: You are looking at unofficial results. Wait until the results are official, and then take another look at these events.